Five Expert Tips for Succeeding with Big Data Analytics

Previously, I shared how some executives are skeptical about Big Data analytics and its ability to match their own business intuition.

This made me wonder: How do some leaders find that Big Data analytics actually enlightens their business behavior? To help you find the path, I’ve compiled five expert tips that may illuminate your Big Data analytics projects.

Tip 1: New analytics often requires new behaviors. Michael Schrage, a research fellow at MIT Sloan School’s Center for Digital Business, says in his discussions with companies, those who struggle or achieve only moderate outcomes tend to use Big Data analytics primarily for decision support. By contrast, Big Data achievers leverage Big Data to change their conversations.

In a Harvard Business School post (registration required), Schrage specifically recommends encouraging more sharing and collaborative work, rethinking or adding business processes, and re-evaluating existing incentives.

Tip 3. Increase analytical skills across the organization. Analytics will require some level of retraining at all levels, McKendrick says, if it’s going to be transformative instead of merely “a support” for existing practices.

“A game plan for assembling and integrating data is essential,” advises a recent McKinsey Quarterly article. “Critical data may reside in legacy IT systems that have taken hold in areas such as customer service, pricing, and supply chains. Complicating matters is a new twist: Critical information often resides outside companies, in unstructured forms such as social-network conversations.”

One take-away from these tips: Big data analytics is not just a larger version of BI. BI excels at reporting and compliance — but for Big Data, these are low-hanging fruits, one CIO told Schrage.

“The most interesting tensions and arguments consistently revolved around whether the organization would reap the greatest returns from using analytics to better optimize existing process behaviors or get people to behave differently,” writes Schrage. “But the rough consensus was that the most productive conversations centered on how analytics changed behaviors rather than solved problems.”

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